Urinary tract infection (UTI) is a common and costly disease that tends to recur in women despite current antibiotic therapies. Recent studies in a mouse model of UTI suggest that some recurrent UTIs are due to an intracellular reservoir of uropathogenic E. coli that forms in the bladder epithelium. A genetic and molecular understanding of how bacteria enter and persist in these intracellular reservoirs would lead to new therapeutic targets. However, exploratory studies of these intracellular bacteria are technically difficult in mice. This proposal will use a recently published method to study the molecular role of one gene, fimH, during intracellular infection. To begin identifying other genes important for intracellular infection, a computational screen for genes under positive selection will be used. Genes important for infection should be evolving under positive selection;this proposal will experimentally validate the hypothesis that screening for positively selected genes provides a novel and complementary method for identifying genes that are important during infection in vivo. Validation of computational predictions will be done for a positively selected gene known to be critical for infection (fimH) and for 29 other genes that are predicted by a computational screen to be under positive selection in uropathogenic E. coli. Mutations in these genes will be tested for decreased fitness in an experimental mouse UTI model, which would indicate that these computationally identified genes are indeed important for in vivo infections. These genes will then be evaluated for a role in intracellular stages of infection, hopefully leading to better treatments for recurrent UTI. These experiments will (1) identify new potential therapeutic targets for further UTI research;(2) validate the utility of computational screens for positive selection in pathogenic bacteria;and (3) establish the power, accuracy, and relevance of molecular evolution theory and algorithms for in vivo studies. PUBLIC HEALTH RELEVANCE: Urinary tract infection (UTI) is a common and costly disease that tends to recur in women despite current treatments. Recurrent UTI may be caused by bacteria that remain in the bladder despite treatment. This proposal uses computational analyses and mouse experiments to understand how bacteria remain in the bladder, resulting in new therapeutic targets and strategies for recalcitrant, recurrent UTI.